OBB-PBD extends parallel box decoding to oriented aerial boxes
Reported rotIoU on the full 6139-record AVVG test set rises from 0.1253 zero-shot to 0.303.
Stories per day · 30 days
2 RSS
8 stories, newest first · one card per story
Stories tagged #parallel-decoding
Next-Concept Modeling: Fast, Parallel Coarse-to-Fine Text Generation
Next-Concept Modeling generates text coarse-to-fine in parallel, up to 31 times faster than diffusion language models.
ALoDLM: Adaptively Looped Diffusion Language Models
ALoDLM allocates diffusion-model computation by token difficulty and beats matching autoregressive baselines.
GroundAnything: Reconciling Parallel Decoding with Precise Visual Grounding at Flash Speed
GroundAnything, a 4B model, pairs parallel diffusion decoding with precise visual grounding and large inference speedups.
Flash-dLLM: IO-Aware KV Caching and Parallel Decoding for Fast, Memory-Efficient Diffusion LLMs
Flash-dLLM speeds diffusion LLM inference with I/O-aware KV caching and parallel draft-and-verify decoding.
Flash-dLLM: IO-Aware KV Caching and Parallel Decoding for Fast, Memory-Efficient Diffusion LLMs
Flash-dLLM accelerates diffusion LLM inference with I/O-aware KV caching, up to 11 times faster than Elastic-Cache.
dQwen3.5: Hybrid-Attention Diffusion Language Models
Researchers adapt Qwen3.5 hybrid-attention backbones (0.8B-9B) into diffusion language models, reaching training loss in half the tokens versus full attention.
Unlocking Lossless Speedups in LLMs via Discrete Diffusion
Uno pairs autoregressive LLMs with lightweight diffusion weights to draw multiple tokens in parallel, delivering up to 3x lossless speedup without a draft model.